• 한국전산구조공학회:학술대회논문집
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• 한국전산구조공학회 2004년도 봄 학술발표회 논문집
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• pp.373-380
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• 2004

This paper presents the feasibility of an impedance-based damage detection technique using piezoelectric (PZT) transducers for civil infrastructures such as steel bridges. The impedance-based damage detection method is based on monitoring the changes in the electrical impedance. Those changes in the electrical impedance are due to the electro-mechanical coupling property of the piezoelectric material and structure. An effective integrated structural health monitoring system must include a statistical process of damage detection that is automated and real time assessment of damage in the structure. Once measured, damage sensitive features from this impedance change can be statistically quantified for various damage cases. The results of the experimental study on three kinds of structural members show that cracks or loosened bolts/nuts near the PZT sensors may be effectively detected by monitoring the shifts of the resonant frequencies. The root mean square (RMS) deviations of impedance functions between before and after damages were also considered as a damage indicator. The subsequent statistical methods using the impedance signature of the PZT sensors were investigated.

• 한국터널지하공간학회 논문집
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• 제15권1호
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• pp.25-31
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• 2013

본 논문은 지하철 터널 유지관리 계측센서의 총 손망실율을 산정하기 위해 국내와 국외의 지하철 터널구조물에 설치되어 운영 중에 있는 유지관리 계측센서의 손망실 현황을 조사하고 분석을 실시하였다. 지하철 터널 유지관리 계측센서 설치 후 5~6년 경과된 시점을 기준하여 총 손망실율은 서울지하철5,6,7호선에서 14.2%, 서울지하철9호선1단계구간에서 14.8%, 영국의 Channel tunnel에서 13.9%로 모두 15%에 근접하게 나타났다. 따라서 지하철 터널 유지관리 계측센서의 총 손망실율은 잠정적으로 15%로 설정하여 설계에 반영하는 것이 타당한 것으로 판단되며, 향후 장기간의 경과년수에 따른 계측항목별 손망실율 연구가 필요할 것으로 판단된다.

• 한국구조물진단유지관리공학회 논문집
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• 제14권1호
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• pp.165-174
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• 2010

본 논문에서는 실물 콘크리트 거더 교량의 가속도 응답 신호를 이용하여 구조물의 상태변화를 경보한 후 그 위치 변화를 검색하는 2단계 구조건전성 모니터링 체계를 제시하였다. 먼저, 2경간 연속 콘크리트 거더 교량인 미호천교를 대상교량으로 선정하였으며, 볼링공을 이용한 강제진동 실험으로부터 동특성을 추출하였다. 다음으로, 미호천교의 2단계 구조건전성 모니터링 체계 구축을 위한 손상 발생 경보 및 손상 위치 검색 기법들을 선정하였다. 손상 경보 기법으로는 시간영역 특징을 이용하는 자기회귀모델과 주파수응답함수의 상관계수, 주파수응답비보증지수를 선정하였다. 손상 위치 검색 기법으로는 모드변형에너지기반 손상지수법을 선정하였다. 마지막으로, 덤프트럭을 이용한 정적 재하 실험을 통해 2단계 손상 모니터링 체계의 적합성을 검증하였다.

• 한국측량학회지
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• 제30권4호
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• pp.369-377
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• 2012

최근 IT기술의 발달과 공간정보기술의 고도화는 방재분야에 있어서 효과적인 피해조사 기술 개발의 필요성을 증대시키고 있다. 자연재해에 효과적으로 대응하고, 복구계획을 수립하기 위해서는 신속한 피해조사가 필요하며, 이러한 점에서 UAV는 신속한 피해조사를 위한 유용한 수단이 될 수 있다. 본 연구에서는 효율적인 자연재해 피해조사를 위한 UAV 기반 실시간 공중자료획득시스템의 활용성을 평가하고자 하였다. 시스템의 적용성 평가를 위해 정확도 분석을 수행하였으며, 국내 규정을 바탕으로 재난 유형을 구분하여 재해 유형별로 시스템을 적용한 피해조사의 활용성을 평가하였다. 연구 결과, 주택피해, 농경지 및 농림시설 피해, 공공시설 피해 등의 피해조사가 가능하였다. 향후 다양한 자연재해 현장을 대상으로 실시간공중자료획득시스템을 통해 취득된 영상자료를 활용함으로써 효율적인 자연재해 피해조사 및 복구계획 수립이 가능할 것이다.

• Smart Structures and Systems
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• 제18권3호
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• pp.501-523
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• 2016

Electromechanical impedance (EMI) based structural health monitoring is performed by measuring the variation in the impedance due to the structural local damage. The impedance signals are acquired from the piezoelectric patches that are bonded on the structural surface. The impedance variation, which is directly related to the mechanical properties of the structure, indicates the presence of local structural damage. Two traditional EMI-based damage detection methods are based on calculating the difference between the measured impedance signals in the frequency domain from the baseline and the current structures. In this paper, a new structural damage detection approach by analyzing the time domain impedance responses is proposed. The measured time domain responses from the piezoelectric transducers will be used for analysis. With the use of the Time Frequency Autoregressive Moving Average (TFARMA) model, a damage index based on Singular Value Decomposition (SVD) is defined to identify the existence of the structural local damage. Experimental studies on a space steel truss bridge model in the laboratory are conducted to verify the proposed approach. Four piezoelectric transducers are attached at different locations and excited by a sweep-frequency signal. The impedance responses at different locations are analyzed with TFARMA model to investigate the effectiveness and performance of the proposed approach. The results demonstrate that the proposed approach is very sensitive and robust in detecting the bolt damage in the gusset plates of steel truss bridges.

• Smart Structures and Systems
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• 제15권2호
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• pp.395-408
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• 2015

This study aims to propose a Bayesian approach to consider changes in temperature and vehicle weight as environmental and operational factors for vibration-based long-term bridge health monitoring. The Bayesian approach consists of three steps: step 1 is to identify damage-sensitive features from coefficients of the auto-regressive model utilizing bridge accelerations; step 2 is to perform a regression analysis of the damage-sensitive features to consider environmental and operational changes by means of the Bayesian regression; and step 3 is to make a decision on the bridge health condition based on residuals, differences between the observed and predicted damage-sensitive features, utilizing 95% confidence interval and the Bayesian hypothesis testing. Feasibility of the proposed approach is examined utilizing monitoring data on an in-service bridge recorded over a one-year period. Observations through the study demonstrated that the Bayesian regression considering environmental and operational changes led to more accurate results than that without considering environmental and operational changes. The Bayesian hypothesis testing utilizing data from the healthy bridge, the damage probability of the bridge was judged as no damage.

• Smart Structures and Systems
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• 제14권5호
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• pp.917-942
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• 2014

Multivariate statistics based damage detection algorithms employed in conjunction with novel sensing technologies are attracting more attention for long term Structural Health Monitoring of civil infrastructure. In this study, two practical data driven methods are investigated utilizing strain data captured from a 4-span bridge model by Fiber Bragg Grating (FBG) sensors as part of a bridge health monitoring study. The most common and critical bridge damage scenarios were simulated on the representative bridge model equipped with FBG sensors. A high speed FBG interrogator system is developed by the authors to collect the strain responses under moving vehicle loads using FBG sensors. Two data driven methods, Moving Principal Component Analysis (MPCA) and Moving Cross Correlation Analysis (MCCA), are coded and implemented to handle and process the large amount of data. The efficiency of the SHM system with FBG sensors, MPCA and MCCA methods for detecting and localizing damage is explored with several experiments. Based on the findings presented in this paper, the MPCA and MCCA coupled with FBG sensors can be deemed to deliver promising results to detect both local and global damage implemented on the bridge structure.

• Structural Monitoring and Maintenance
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• 제7권1호
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• pp.13-25
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• 2020

One of the most important aspects in structural health monitoring is the detection of fatigue damage. Structural components such as heavy-duty bolts work under high dynamic loads, and thus are prone to accumulate fatigue damage and cracks may originate. Those heavy-duty bolts are used, for example, in wind power generation and mining equipment. Therefore, the investigation of new and more effective monitoring technologies attracts a great interest. In this study the acoustic emission (AE) technology was employed to detect incipient damage during fatigue testing of a M36 bolt. Initial results showed that the AE signals have a high level of background noise due to how the load is applied by the fatigue testing machine. Thus, an advanced signal processing method in the time-frequency domain, the Hilbert-Huang Spectrum (HHS), was applied to reveal AE components buried in background noise in form of high-frequency peaks that can be associated with damage progression. Accordingly, the main contribution of the present study is providing insights regarding the detection of incipient damage during fatigue testing using AE signals and providing recommendations for further research.

• Smart Structures and Systems
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• 제6권7호
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• pp.811-833
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• 2010

Vibration control and health monitoring of building structures have been actively investigated in recent years but treated separately according to the primary objective pursued. This paper presents a general approach in the time domain for integrating vibration control and health monitoring of a building structure to accommodate various types of control devices and on-line damage detection. The concept of the time-domain approach for integrated vibration control and health monitoring is first introduced. A parameter identification scheme is then developed to identify structural stiffness parameters and update the structural analytical model. Based on the updated analytical model, vibration control of the building using semi-active friction dampers against earthquake excitation is carried out. By assuming that the building suffers certain damage after extreme event or long service and by using the previously identified original structural parameters, a damage detection scheme is finally proposed and used for damage detection. The feasibility of the proposed approach is demonstrated through detailed numerical examples and extensive parameter studies.

• Structural Monitoring and Maintenance
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• 제7권3호
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• pp.261-281
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• 2020

Civil structures may experience progressive deterioration and damage under environmental and operational conditions over their service life. Finite element (FE) model updating method is one of the most important approaches for damage identification in structures due to its capabilities in structural health monitoring. Although various damage detection approaches have been investigated on structures, there are limited studies on large-sized space structures. Thus, this paper aims to investigate the applicability and efficiency of sensitivity-based FE model updating framework for damage identification in large space structures from a distinct point of view. This framework facilitates modeling and model updating in large and geometric complicated space structures. Considering sensitivity-based FE model updating and vibration measurements, the discrepancy between acceleration response data in real damaged structure and hypothetical damaged structure have been minimized through adjusting the updating parameters. The feasibility and efficiency of the above-mentioned approach for damage identification has finally been demonstrated with two numerical examples: a flat double layer grid and a double layer diamatic dome. According to the results, this method can detect, localize, and quantify damages in large-scaled space structures very accurately which is robust to noisy data. Also, requiring a remarkably small number of iterations to converge, typically less than four, demonstrates the computational efficiency of this method.